The purpose of this study is to investigate whether the entropy of acoustic emissions (AE), generated both by cumulated damage and damage growth, can be used for the condition monitoring of carbon fiber reinforced polymers (CFRP) subjected to multi-axial cyclic loading. The average evolution of four entropies is studied; two in the time domain and two in the frequency domain. The AE used for studying the average evolution is acquired during fatigue testing of 75 nominally identical CFRP prosthetic feet. The results show that the evolutions of the two entropies estimated in the time domain correlate well with the evolution of the AE hit count. One of time domain entropies is computationally simpler than the AE hit count procedure and uses the whole AE signal. Further research is needed to answer if it is a better alternative to conventional AE hit counting.

We conducted the waveform analysis of acoustic emission (AE) signals to study the dynamic behavior of materials deformed or transformed; namely, two types of martensitic transformation in Cu-Ni-Al shape-memory-alloy (SMA) single crystals during tensile deformation that produce different martensitic structures. The AE source behavior is expected to be of shear. We simulated AE signals due to martensitic transformation using a shear-wave transducer as the artificial source. Results of AE waveform analysis in Cu-Al-Ni SMA single crystals are compared with the simulation results. The martensite with a simpler stacking structure exhibits faster transformation behavior.

The article is the addition to the article [1] and describes some results of AE laboratory at an oil refinery during the past 17 years. Some problems of AE application for testing industrial pressure vessels and possible solutions of these problems are presented. On the pressure vessel tests, it is shown that AE testing is the essential factor for increasing of the efficiency of complex NDT of dangerous industrial hardware.

Simple noise level monitoring systems, which are currently used around airports to create a noise map in residential areas, are unable to identify source frequencies and their impact on the environment. This article presents dominant frequencies during aircraft approaches of the SaintExupéry Lyon International Airport (France), and analyzes the evidence of impact on the environment. The main objective is the characterization of the most dominant frequencies emitted during approach operations, and the diagnosis of frequencies having a negative impact on populations living around the airport. A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. A study of the emission angle has been completed and a classification period depending on the noise level has been achieved. Development of a deDopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. It is shown that correcting for Doppler amplitude and frequency can give some idea about source directivity. The obtained results provide additional information placing the results of theoretical models in their context, and will help validate and extend certain methods of calculating the propagation of aircraft noise. They have the potential to quantify environmental quality around the airports. The precise measured frequencies during the operations can be treated by passive or active control systems developed by aircraft manufacturers.

The universal A-Line software of Interunis is an integral part of acoustic emission (AE) systems and is designed for solving various problems of data processing and visualization, and for full-scale control of the system hardware component. Simultaneously with development of new generations of the A-Line AE systems the software has been improved, is based on the upto-date information technologies and programming methods, incorporating real AE applications experience of internal and external users of the A-Line family AE systems. This paper briefly describes the significant functional features of program features implemented recently; a method of approximate location of AE sources using a free-form sensor array on surfaces of thin-wall vessels, information statistical criterion for division of AE sources according to the type and method for evaluating the distance from a sensor to an estimated source on the basis of waveletanalysis of AE impulse taking into account the dispersion dependencies of group velocities of Lamb waves.

The technological progress in power systems requires the application of new solutions that will meet higher specifications than the currently used, in all parts of equipment design. This also refers to the external castings of power devices, especially those operating over a long time under high-pressure SF6 dielectric gas. Increased requirements include a 20% increase of the SF6 operating pressure and the same increase of the destructive test pressure, and simultaneous reduction of the casting weight. In this paper we present test results of casting materials and strength calculations for the implemented changes in design. The optimization and design verification activities included acoustic emission (AE) measurements performed during a hydraulic pressure test. The results obtained allowed to determine the locations and pressure values, at which the plastic strain began to occur, and the position of the final failure.

Acoustic emission (AE) is one of an evolving array of inspection methods being applied to bridge inspection. The authors have used it as one of an ensemble of methods for bridge condition assessment and to prescribe maintenance follow-up actions with major financial implications. Over twenty years of AE application in risk-informed approach to maintenance management, in which AE has been applied to over 400 bridges out of an ensemble of over 1000 bridges in the authors bridge maintenance experience, has clearly established a role for AE. This experience has also provided a combination of experimental and theoretical input for enhanced interpretation consistent with established codes and standards. Positioning of AE in the risk-informed maintenance management context, its application in bridge inspection and interpretation through the recommendations it provides and case-study examples are described.

Discovery of a 130 mm (5 in) long full-depth crack in a fracture-critical member of a large steel through truss bridge led to the deployment of acoustic emission (AE) testing in concert with other, more traditional, non-destructive evaluation methods. While AE continues to gain acceptance as a method for evaluating civil structures, the application of AE testing to steel bridge details that are fully exposed to the elements and difficult to reach presents some special challenges; as such, AE work typically has been contingent on favorable field conditions. In this study, a custom weatherproof enclosure and robust communication and control methods were deployed to obtain useful AE data in this environment. First-hit channel analysis, planar location, and spatial/temporal clustering analysis were used to determine if the crack was actively growing. The AE results were validated by corroborating results from ultrasonic testing and radiography. Introduction The John F. Kennedy Memorial Bridge, a large cantilever through truss bridge opened in 1963, carries Interstate 65 across the Ohio River between Louisville, Kentucky and Jeffersonville, Indiana. According to a count by the Kentucky Transportation Cabinet (2003), the bridge carries over 120,000 vehicles per day. Inspections revealed a 130 mm (5 in) long fulldepth transverse crack in the horizontal web in a tension region of the top chord on the east truss, the site indicated in Fig. 1a. A partial-depth saw cut and an irregularly shaped hole of unclear origin are present along the web-flange weld, and a 25 mm (1 in) diameter stop hole is present at the end of the crack, as shown in Fig. 1b. The crack is in a fracture-critical member, meaning that fracture of the member would likely cause partial or complete failure of the bridge. Acoustic emission (AE) monitoring was employed in conjunction with other non-destructive evaluation techniques, including ultrasonic testing and radiography, to help detect and characterize any indications that the crack might jump the stop hole or propagate into the vertical flange of the m

A system, based on acoustic emission (AE) monitoring technique, has been studied at Kielce University of Technology for several years. A reference-signals database has been prepared based on laboratory tests on samples, beams and full-scale girders. The developed reference data has been verified during field monitoring of prestressed and post-tensioned concrete bridges. Some phenomena, which are usually very difficult or even impossible to discover by the traditional methods, were detected by this system.

Several limitations and difficulties exist in the inspection and maintenance of underground pipelines that cannot use pigs (pipeline inspection gauges). Leaking is unavoidable in such buried pipelines and poses serious problem to the environment as well as the pipeline owners. Pipeline leakages are usually apparent either when the pressure is dropping for no other obvious reason or when valuable product is lost. However, even in the best-case scenario, where the operators can isolate specific pipeline sections suspected to leak, it is often the case that the operators cannot reliably locate the exact position of the leak so as to take corrective measures. Acoustic emission (AE) is an excellent tool for detecting and locating leaks in buried pipelines. Access to the pipeline is required only locally for mounting AE sensors. Pipeline is pressurized and AE tested in 600-to-1000-m-long sections at a time. The AE sensors detect the turbulent flow at the leak orifice, and with the use of digital AE systems and specialized software, the position of the leak is provided. The present paper deals with the technical description and the physics of the AE leak detection technique, presents the advantages, limitations and requirements of the method, describes the necessary functions of AE equipment for performing such a task, and, finally, reports on several case-studies of successful leak detection and location of buried pipelines. The case studies cover both new and in-service buried pipelines of different sizes.

This research applies the nondestructive evaluation (NDE) methodology used in aviation to monitor structural steel in the form of axially loaded notched specimens for fatigue-life prediction. It applies acoustic emission (AE) nondestructive testing (NDT) to monitor the development of fatigue-crack growth and employs a Kohonen self-organizing map (SOM) artificial neural network (ANN) to identify the failure mechanisms in A572-G50 steel. In addition, a backpropagation neural network (BPNN) was utilized to perform fatigue-life prediction from the first quarter (0-25%) of the experimental fatigue life or cyclic life data. A second BPNN was created for prediction based on the third quarter (50-75%) of fatigue-life data. Testing of axially loaded notched specimens was completed and experimental results were used to generate the characteristic alternating stress versus fatigue life (S-N) curves. These results were compared to those calculated from linear elastic fracture mechanics (LEFM) using the damage tolerance analysis software Air Force Growth (AFGROW). AE data generated from fatigue-crack growth were also processed using a Kohonen SOM neural network to categorically identify the failure modes of plastic deformation plus plane-strain and plane-stress fracture. Fatigue-prediction analysis focused on developing a BPNN for high-cycle fatigue (HCF) prediction from AE amplitude histogram distributions. This network provided prediction results within ?20% for first quarter data and ?12% for third quarter data predictions, respectively, which demonstrated the feasibility of making fatigue-life predictions in steel structures from AE data.

A method for cutting-blade pressure adjustment during dynamic cutting of paperboard is introduced in a combination of resin bridgeless die and high-carbon center-bevel blade. In this method, the blade bottom is embedded in a dead-end bridgeless die slot where unbalance of blade cutting will be compensated from the sinking of the blade bottom. This paper reports on the relationship between the acoustic emission (AE) and blade-cutting pressure balance in a crank machine under quasi-static reciprocal motion. Two kinds of blade bottom condition with bottom thickness of 0.71 mm were experimented and their results on force difference and AE signals during cutting were compared. Through this research, the proposed measurement technique was found reliable in detecting the characteristics of blade-pressure adjustment, and the correlation between the AE signal amplitude, the frequency spectrum and the blade shimming condition.

Carbon-carbon (C/C) composites with different densities (1.8, 1.35, 0.8 g/cm3), produced by chemical vapor infiltration (CVI) were tested mechanically under quasi-static loading in bending mode of uniform and notched beams. Acoustic emission (AE) technique was used to track the mechanical threshold parameters as well as to characterize the damage build-up profile to fracture. In both states of stress (uniform and tri-axial), threshold values detected by AE activity indicated the damage onset. The sensitivity of the AE method to the density changes was apparent by variations of the threshold values. Decreasing the density from 1.8 to 0.8 g/cm3 decreases the thresholds values (th, KIth) from 25 to 2 MPa and from 0.8 to 0.1 MPa?m1/2, respectively. Three stages in damage evolution to fracture were observed: Stage I, with no AE activity, Stage II, gradual/linear growth in AE counts up to an abrupt jump and Stage III with exponential increase in AE counts. Similarity in profile and threshold value were found between the cumulative AE counts vs. strain data and the crack density vs. strain predicted by micro mechanical model, indicating the importance of using AE in monitoring the damage evolution in composites with regard to structural integrity aspect. Wave analysis using fast Fourier transform (FFT) and short-time fast Fourier transform (ST-FFT) points out four possible failure micro-mechanisms: multilayer cracking, breaking of fiber bundles, interfacial matrix de-bonding and micro-crack growth. Breaking of fiber bundles was found to be the major damage mechanism for the low density C/C composite.

It is important to evaluate the integrity of composite overwrapped pressure vessels (COPVs) used for space applications. In this study, applicability of acoustic emission (AE) monitoring to the integrity evaluation of COPV materials was evaluated by using coupon-level specimens. It was found that by evaluating emissions during load-hold and relationship between AE signal peak amplitude and duration, damage occurrences during the test can be monitored. We also found that Kaiser effect and Felicity effect can be used for evaluating previously induced damages. Detectable minimum damage size for previously induced damage by AE method may be same or less than those by ultrasonic testing.

The characteristics of stress waves accompanying the collisions of rigid bodies are investigated. It is shown that high-frequency transducer of acoustic emission apparatus transforms initial impact perturbation into two separate signals, arriving with delay equal to impact duration. AE signals are generated at the moments corresponding to discontinuities of the derivative of surface displacement function of impacting bodies; i.e., at the initial moment of loading and the final moment of contact. It is shown experimentally that different Lamb modes recorded in the far-field zone of the impact source contain double signals arriving with the same delay as the signals in the near-field zone. The relationship between the AE waveform and the impact parameters determined in the study enables one to estimate physical characteristics of impact, such as surface displacement, contact time and impact force. Practical significance of these findings for evaluation of structural integrity is discussed.

Rayleigh or surface waves in acoustic emission (AE) applications were examined for nominal 25-mm thick steel plates. Pencil-lead breaks (PLBs) were introduced on the top and bottom surfaces as well as on the plate edge. The plate had large transverse dimensions to minimize edge reflections arriving during the arrival of the direct waves. An AE data sensor was placed on the top surface at both 254 mm and 381 mm from the PLB point or the epicenter of the PLB point. Also a trigger sensor was placed close to the PLB point. The signals were analyzed in the time domain and the frequency/time domain with a wavelet transform. For most of the experiments, the two data sensors had a small aperture (about 3.5 mm) and a high resonant frequency (about 500 kHz). These sensors effectively emphasized a Rayleigh wave relative to Lamb modes. In addition, finite-element modeling (FEM) was used to examine the presence or absence of Rayleigh waves generated by dipole point sources buried at different depths below the plate top surface. The resulting out-of-plane displacement signals were analyzed in a fashion similar to the experimental signals for propagation distances of up to 1016 mm for out-of-plane dipole sources. Rayleigh waves were generated in the experiments for all three locations of PLBs. In the case of the bottom surface PLBs, the Rayleigh wave propagated to the plate edge, up the edge and then along the plate top surface to the sensors. Due to the time delay from the propagation up the edge to the plate surface, Rayleigh waves from edge PLBs resulted in a strong signal that interfered with a straightforward analysis of the intense frequency/time regions of the Lamb modes from these source positions. The FEM results for the out-of-plane dipoles showed that the surface outof-plane displacement amplitude of the Rayleigh wave decayed relative to the Lamb mode amplitudes as the depth of the source below the surface pseudo sensors increased. A Rayleigh wave was not observed for sources deeper than about 23 % of the plate thickness. In contrast, for a case of an in-plane buried

Fatigue tests of bovine cortical bone were carried out. Compressive stress was applied along longitudinal axis of bones and fracture surfaces were parallel to the loading direction. Damage accumulation during tests was monitored by the measurements of acoustic emission (AE) signals and ultrasonic wave velocity. For the static compression test, specimens fractured catastrophically and the most of AE signals were detected close to final fracture. On the other hand, AE events increased and wave velocity decreased gradually during fatigue fracture of bone. A majority of AE signals were detected during unloading and they formed characteristic AE bands. AE wavelet analysis demonstrated that the peak frequencies of unloading AE, as well as loading AE, were equivalent to the resonant frequency along the specimen thickness. Finally, it is strongly suggested that microcrack extension due to wedging effect of debris took place during unloading in the fatigue process of cortical bone.

Plastic instabilities are investigated in iron with different purity by means of acoustic emission (AE) power spectral analysis. Special attention is paid to AE accompanying the yield drop followed by Lüders-band propagation and macroscopic strain localization associated with necking followed by crack nucleation and propagation. Both the Lüders instability and necking belong to the same generic type strain-softening instability although the former refers to the socalled propagative instability while the latter is static. In both cases, significant shift of the power spectral density towards low frequencies is observed and discussed.

In order to characterize the generations of electromagnetic emission (EME) and cracks created inside the materials in detail, we measured EME under monotonously increasing and repeated compressive loading of the granite sample. In the loading tests, AE signals were simultaneously measured with the EME signals, so that the generation of EME could be directly compared with the entire fracture process of the rock sample estimated by AE. In the uniaxial compressive tests, the sample was loaded at different displacement speeds from 0.02 to 0.5 mm/min. In comparison with AE, the number of EME events discriminated is lower, because of a lower signal-to-noise ratio of EME channel. The relationship between signal amplitudes of EME and AE suggests the existence of the correlation between AE and EME. The EME signals with the larger amplitude are associated with the AE signals of larger amplitude. Dispersion observed in the EME vs. AE signal amplitude plots is related to crack orientation with respect to EME electrodes. This paper also demonstrates that the simultaneous measurement of AE and EME would be useful for estimating the rock in-situ stress, as an example.

Previous studies by the authors have revealed that AE multiplets, which are groups of events with closely similar waveforms, can be used effectively to precisely delineate structures inside artificially stimulated geothermal, oil, and gas reservoirs and to determine their response to the stimulation. The similarity of the waveforms among the collected AE events, which are evaluated at some fixed frequency, can be represented by a product of the transfer functions of the source, the earth, and the receiver/recorder. Meanwhile, the low-pass characteristics of the earth transfer function appear more strongly in the coda, where reflected, refracted, mode-converted, and scattered waves arrive randomly at the receiver. This feature of the time and frequency characteristics of the AE signals led to the idea of identifying multiplets in the time and frequency domains. This paper presents results from multiplet identification in the time and frequency domains by using data sets collected at engineered geothermal development sites at Cooper Basin, Australia, and Basel, Switzerland, demonstrating that AE multiplets from different physical phenomena can be clustered by their identification in the time and frequency domains.